{"id":"https://openalex.org/W4292823745","doi":"https://doi.org/10.1002/env.2755","title":"Clustering of bivariate satellite time series: A quantile approach","display_name":"Clustering of bivariate satellite time series: A quantile approach","publication_year":2022,"publication_date":"2022-08-22","ids":{"openalex":"https://openalex.org/W4292823745","doi":"https://doi.org/10.1002/env.2755"},"language":"en","primary_location":{"id":"doi:10.1002/env.2755","doi":"https://doi.org/10.1002/env.2755","is_oa":false,"landing_page_url":"https://doi.org/10.1002/env.2755","pdf_url":null,"source":{"id":"https://openalex.org/S17114410","display_name":"Environmetrics","issn_l":"1099-095X","issn":["1099-095X","1180-4009"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","jufo-2","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Environmetrics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.11682","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034758336","display_name":"Victor Muthama Musau","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I3131411328","display_name":"Kirinyaga University","ror":"https://ror.org/00geck193","country_code":"KE","type":"education","lineage":["https://openalex.org/I3131411328"]}],"countries":["KE"],"is_corresponding":true,"raw_author_name":"Victor Muthama Musau","raw_affiliation_strings":["Department of Pure and Applied Sciences, Kirinyaga University, Kerugoya, Kenya"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Pure and Applied Sciences, Kirinyaga University, Kerugoya, Kenya","institution_ids":["https://openalex.org/I3131411328"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009351038","display_name":"Carlo Gaetan","orcid":"https://orcid.org/0000-0002-1361-9959","observed_orcids":["https://orcid.org/0000-0002-1361-9959"]},"institutions":[{"id":"https://openalex.org/I149461666","display_name":"Ca' Foscari University of Venice","ror":"https://ror.org/04yzxz566","country_code":"IT","type":"education","lineage":["https://openalex.org/I149461666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Carlo Gaetan","raw_affiliation_strings":["Dipartimento di Scienze Ambientali, Informatica e Statistica Universit\u00e0 Ca' Foscari \u2010 Venezia Venice Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Scienze Ambientali, Informatica e Statistica Universit\u00e0 Ca' Foscari \u2010 Venezia Venice Italy","institution_ids":["https://openalex.org/I149461666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056789152","display_name":"Paolo Girardi","orcid":"https://orcid.org/0000-0001-8330-9414","observed_orcids":["https://orcid.org/0000-0001-8330-9414"]},"institutions":[{"id":"https://openalex.org/I149461666","display_name":"Ca' Foscari University of Venice","ror":"https://ror.org/04yzxz566","country_code":"IT","type":"education","lineage":["https://openalex.org/I149461666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Girardi","raw_affiliation_strings":["Dipartimento di Scienze Ambientali, Informatica e Statistica Universit\u00e0 Ca' Foscari \u2010 Venezia Venice Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Scienze Ambientali, Informatica e Statistica Universit\u00e0 Ca' Foscari \u2010 Venezia Venice Italy","institution_ids":["https://openalex.org/I149461666"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034758336"],"corresponding_institution_ids":["https://openalex.org/I3131411328"],"apc_list":{"value":4200,"currency":"USD","value_usd":4200},"apc_paid":null,"fwci":0.1419,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.39889266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"33","issue":"7","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.6348000168800354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.6348000168800354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.31690001487731934,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.030799999833106995,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quantile-regression","display_name":"quantile regression","score":0.8709999918937683},{"id":"https://openalex.org/keywords/model-based-clustering","display_name":"model-based clustering","score":0.8330000042915344},{"id":"https://openalex.org/keywords/asymmetric-laplace-distribution","display_name":"asymmetric Laplace distribution","score":0.9980000257492065},{"id":"https://openalex.org/keywords/satellite-time-series","display_name":"satellite time series","score":0.6549999713897705},{"id":"https://openalex.org/keywords/temporal-dynamics","display_name":"temporal dynamics","score":0.7139999866485596},{"id":"https://openalex.org/keywords/gulf-of-gabes","display_name":"Gulf of Gab\u00e8s","score":0.8730000257492065},{"id":"https://openalex.org/keywords/water-quality-monitoring","display_name":"water quality monitoring","score":0.3880000114440918}],"concepts":[{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.7962368726730347},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.7421205043792725},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6385139226913452},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6283806562423706},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5691161155700684},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.513237714767456},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4807865023612976},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4154629111289978},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14006826281547546},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1002/env.2755","doi":"https://doi.org/10.1002/env.2755","is_oa":false,"landing_page_url":"https://doi.org/10.1002/env.2755","pdf_url":null,"source":{"id":"https://openalex.org/S17114410","display_name":"Environmetrics","issn_l":"1099-095X","issn":["1099-095X","1180-4009"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","jufo-2","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Environmetrics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2207.11682","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.11682","pdf_url":"https://arxiv.org/pdf/2207.11682","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:iris.unive.it:10278/5001251","doi":null,"is_oa":false,"landing_page_url":"https://hdl.handle.net/10278/5001251","pdf_url":null,"source":{"id":"https://openalex.org/S4306402336","display_name":"ARCA (Universit\u00e0 Ca' Foscari Venezia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I149461666","host_organization_name":"Ca' Foscari University of Venice","host_organization_lineage":["https://openalex.org/I149461666"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.48550/arxiv.2207.11682","doi":"https://doi.org/10.48550/arxiv.2207.11682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2207.11682","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2207.11682","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.11682","pdf_url":"https://arxiv.org/pdf/2207.11682","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4292823745.pdf","grobid_xml":"https://content.openalex.org/works/W4292823745.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W41409100","https://openalex.org/W1249696972","https://openalex.org/W1535685845","https://openalex.org/W1579271636","https://openalex.org/W1702032637","https://openalex.org/W1965267599","https://openalex.org/W1966408116","https://openalex.org/W1980533657","https://openalex.org/W1985870679","https://openalex.org/W1989280111","https://openalex.org/W2015558203","https://openalex.org/W2017606789","https://openalex.org/W2018941747","https://openalex.org/W2029939318","https://openalex.org/W2039447472","https://openalex.org/W2040579578","https://openalex.org/W2045997220","https://openalex.org/W2049607413","https://openalex.org/W2051119716","https://openalex.org/W2053101680","https://openalex.org/W2057765075","https://openalex.org/W2073489855","https://openalex.org/W2075078588","https://openalex.org/W2080177452","https://openalex.org/W2084871407","https://openalex.org/W2087034140","https://openalex.org/W2110813565","https://openalex.org/W2156619449","https://openalex.org/W2156870137","https://openalex.org/W2162136094","https://openalex.org/W2165925147","https://openalex.org/W2174926646","https://openalex.org/W2487122920","https://openalex.org/W2507042954","https://openalex.org/W2551685232","https://openalex.org/W2561066426","https://openalex.org/W2594329014","https://openalex.org/W2744350495","https://openalex.org/W2768002040","https://openalex.org/W2775953301","https://openalex.org/W2799916807","https://openalex.org/W2885647151","https://openalex.org/W2904449810","https://openalex.org/W2938944163","https://openalex.org/W3042914263","https://openalex.org/W3100479874","https://openalex.org/W4235169531","https://openalex.org/W4241653265","https://openalex.org/W4292691288","https://openalex.org/W4399572290"],"related_works":["https://openalex.org/W2507042954","https://openalex.org/W7066354133","https://openalex.org/W7062084451","https://openalex.org/W4392043624","https://openalex.org/W2220854427","https://openalex.org/W2571221080","https://openalex.org/W7125758386","https://openalex.org/W6903763255","https://openalex.org/W2810257535","https://openalex.org/W2747328945"],"abstract_inverted_index":{"Abstract":[0],"Clustering":[1],"has":[2],"received":[3],"much":[4],"attention":[5],"in":[6,30,78,124,168,174,179],"statistics":[7],"and":[8,18,55],"machine":[9],"learning":[10],"with":[11,161],"the":[12,48,52,66,75,109,125,128,132,135,180],"aim":[13,162],"of":[14,24,74,80,127,134,163,176,182],"developing":[15],"statistical":[16],"models":[17],"autonomous":[19],"algorithms":[20],"which":[21],"are":[22],"capable":[23],"acquiring":[25],"information":[26],"from":[27,152],"raw":[28],"data":[29,155],"order":[31,169],"to":[32,41,63,98,119,147,157,170],"perform":[33],"exploratory":[34],"analysis.":[35],"Several":[36],"techniques":[37],"have":[38,59],"been":[39,61],"developed":[40],"cluster":[42,99,111,148],"sampled":[43],"univariate":[44],"vectors":[45],"only":[46],"considering":[47],"average":[49],"value":[50],"over":[51],"whole":[53],"period":[54],"as":[56,69,71],"such":[57],"they":[58],"not":[60],"able":[62],"explore":[64],"fully":[65],"underlying":[67],"distribution":[68,116,126],"well":[70],"other":[72],"features":[73],"data,":[76],"especially":[77],"presence":[79],"structured":[81],"time":[82,101,149],"series.":[83],"We":[84,107,130],"propose":[85],"a":[86,139],"model\u2010based":[87],"clustering":[88],"technique":[89,137],"that":[90],"is":[91,144],"based":[92],"on":[93],"quantile":[94,105],"regression":[95],"permitting":[96],"us":[97,118],"bivariate":[100],"series":[102,150],"at":[103],"different":[104],"levels.":[106],"model":[108],"within":[110],"density":[112],"using":[113],"asymmetric":[114],"Laplace":[115],"allowing":[117],"take":[120],"into":[121],"account":[122],"asymmetry":[123],"data.":[129],"evaluate":[131],"performance":[133],"proposed":[136],"through":[138],"simulation":[140],"study.":[141],"The":[142],"method":[143],"then":[145],"applied":[146],"observed":[151],"Glob\u2010color":[153],"satellite":[154],"related":[156],"trophic":[158,177],"status":[159],"indices":[160],"evaluating":[164],"their":[165],"temporal":[166],"dynamics":[167],"identify":[171],"homogeneous":[172],"areas,":[173],"terms":[175],"status,":[178],"Gulf":[181],"Gabes.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2022-08-24T00:00:00"}
